SVM-based method for the classification of protein sequence as secretory
or non-secretory protein. It consists of different SVM modules based on
different features of proteins such as compositions(Amino acid, physicochemical
prperties, and dipeptide). In addition PSI-BLAST was also used to carry out
similarity-based search. Finally a hybrid approach based SVM module was developed that
encapsulates complete information of a protein sequence that is amino
acid and dipeptide composiiton and PSI-BLAST. This module can classify the protein
sequence between secretory and non-secrtory protein with an accuracy of 83%. Users have
a choice to use any of these module for predcition of their query sequence.

If you are using this webserver, please cite: Garg, A. and Raghava, G. P. S. (2008) A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search. In Silico Biology 8:129-140.